mlsanityData to 14 Oct 2026

A variance modeling framework based on variational autoencoders for speech enhancement

arXiv 1902.01605 ↗First posted 5 Feb 2019cs.SD cs.LG eess.AScited by 33

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Abstract (arXiv)

In this paper we address the problem of enhancing speech signals in noisy mixtures using a source separation approach. We explore the use of neural networks as an alternative to a popular speech variance model based on supervised non-negative matrix factorization (NMF). More precisely, we use a variational autoencoder as a speaker-independent supervised generative speech model, highlighting the conceptual similarities that this approach shares with its NMF-based counterpart. In order to be free of generalization issues regarding the noisy recording environments, we follow the approach of having a supervised model only for the target speech signal, the noise model being based on unsupervised NMF. We develop a Monte Carlo expectation-maximization algorithm for inferring the latent variables in the variational autoencoder and estimating the unsupervised model parameters. Experiments show that the proposed method outperforms a semi-supervised NMF baseline and a state-of-the-art fully supervised deep learning approach.

Key facts. Cited by 33 papers in the map (data through 14 Oct 2026). First posted on arXiv 5 Feb 2019.

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Citing papers per year: 2021: 5; 2022: 13; 2023: 6; 2024: 3; 2025: 4; 2026: 2.

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  1. 2022Speech Enhancement and Dereverberation with Diffusion-based Generative Modelscited by 197
  2. 2022StoRM: A Diffusion-based Stochastic Regeneration Model for Speech Enhancement and Dereverberationcited by 105
  3. 2022Speech Enhancement with Score-Based Generative Models in the Complex STFT Domaincited by 102
  4. 2021Variational Autoencoder for Speech Enhancement with a Noise-Aware Encodercited by 28
  5. 2021Unsupervised Speech Enhancement using Dynamical Variational Auto-Encoderscited by 28
  6. 2021Guided Variational Autoencoder for Speech Enhancement With a Supervised Classifiercited by 12
  7. 2022SRTNet: Time Domain Speech Enhancement Via Stochastic Refinementcited by 12
  8. 2023Diffusion-Based Speech Enhancement with Joint Generative and Predictive Decoderscited by 10
  9. 2021Disentanglement Learning for Variational Autoencoders Applied to Audio-Visual Speech Enhancementcited by 7
  10. 2023SE-Bridge: Speech Enhancement with Consistent Brownian Bridgecited by 7
  11. 2021Switching Variational Auto-Encoders for Noise-Agnostic Audio-visual Speech Enhancementcited by 6
  12. 2022Integrating Statistical Uncertainty into Neural Network-Based Speech Enhancementcited by 4
21 more
  1. 2022Expression-preserving face frontalization improves visually assisted speech processingcited by 4
  2. 2022The impact of removing head movements on audio-visual speech enhancementcited by 3
  3. 2022Deep neural network techniques for monaural speech enhancement: state of the art analysiscited by 3
  4. 2025A Survey of Deep Learning for Complex Speech Spectrogramscited by 3
  5. 2022A Sparsity-promoting Dictionary Model for Variational Autoencoderscited by 2
  6. 2022Learning and controlling the source-filter representation of speech with a variational autoencodercited by 2
  7. 2022Audio-visual speech enhancement with a deep Kalman filter generative modelcited by 2
  8. 2022Fast and efficient speech enhancement with variational autoencoderscited by 2
  9. 2024Sound Source Separation Using Latent Variational Block-Wise Disentanglementcited by 2
  10. 2024Deep Generative Modeling for Identification of Noisy, Non-Stationary Dynamical Systemscited by 2
  11. 2023Partially Adaptive Multichannel Joint Reduction of Ego-noise and Environmental Noisecited by 1
  12. 2023Unsupervised speech enhancement with deep dynamical generative speech and noise modelscited by 1
  13. 2024Selective State Space Model for Monaural Speech Enhancementcited by 1
  14. 2022A weighted-variance variational autoencoder model for speech enhancementcited by 0
  15. 2023Integrating Uncertainty into Neural Network-based Speech Enhancementcited by 0
  16. 2023Self-supervised learning with diffusion-based multichannel speech enhancement for speaker verification under noisy conditionscited by 0
  17. 2025Combining Deterministic Enhanced Conditions with Dual-Streaming Encoding for Diffusion-Based Speech Enhancementcited by 0
  18. 2025SEED: Speaker Embedding Enhancement Diffusion Modelcited by 0
  19. 2025Lightweight Wasserstein Audio-Visual Model for Unified Speech Enhancement and Separationcited by 0
  20. 2026SB-RF: Schr"odinger Bridge Rectified Flow for One-Step Robust Speech Enhancementcited by 0
  21. 2026Test-time adaptation for speech enhancement with an autoregressive speech priorcited by 0